Novel biomarker-based score (SAD-60) for predicting mortality in patients with COVID-19 pneumonia: a multicenter retrospective cohort of 1013 patients

Background: The aim was to explore a novel risk score to predict mortality in hospitalized patients with COVID-19 pneumonia. Methods: This was a retrospective, multicenter study. Results: A total of 1013 patients with COVID-19 were included. The mean age was 60.5 ± 14.4 years, and 581 (57.4%) patients were male. In-hospital death occurred in 124 (12.2%) patients. Multivariate analysis revealed peripheral capillary oxygen saturation (SpO2), albumin, D-dimer and age as independent predictors. The mortality score model was given the acronym SAD-60, representing SpO2, Albumin, D-dimer, age ≥60 years. The SAD-60 score (0.776) had the highest area under the curve compared with CURB-65 (0.753), NEWS2 (0.686) and qSOFA (0.628) scores. Conclusion: The SAD-60 score has a promising predictive capacity for mortality in hospitalized patients with COVID-19.

to the ICU. In-hospital death occurred in 124 (12.2%) patients. A total of 18 patients (14.5%) died during the first week of hospitalization. Demographic characteristics of survived and deceased patients with COVID-19 are available in Table 1.
A nomogram was developed based on four independent predictors in multivariable analysis. The score point of each parameter was determined according to its OR values. The total point, which varied from 0 to 10, was calculated by summing the points obtained from each parameter. The risk of death by total points is demonstrated in the nomogram in Figure 2. The mortality score model was given the acronym SAD-60, representing SpO2, Albumin, D-dimer, age ≥60 years. The SAD-60 score (0.776) had the highest AUC compared with CURB-65 (0.753), NEWS2 (0.686) and qSOFA (0.628) scores ( Figure 3). The risk of death was higher than 75% in patients with more than 8 points and lower than 25% in patients with fewer than 5.5 points.
Additionally, the predictive ability of the SAD-60 score for ICU admission or in-hospital death was assessed and compared with CURB-65, NEWS2 and qSOFA. The results are demonstrated in Figure 4.

Discussion
In this study, we presented a detailed analysis of 1013 patients with COVID-19 pneumonia in a multicenter retrospective cohort study and created a simple prediction model based on two biomarkers of albumin and Ddimer, as well as the clinical features of age and SpO2. The SAD-60 score that was derived from the model in the   present study had a promising predictive capacity for mortality in hospitalized patients with COVID-19. Age [23], SpO2 [11], albumin [24] and D-dimer [25,26] were demonstrated as independent predictors for mortality in patients with COVID-19 in different previous studies. However, to our knowledge, this is the first study to combine these four parameters to predict mortality in hospitalized patients with COVID-19 pneumonia. In multivariate analysis, increased age, SpO2, albumin and D-dimer were associated with about 3.5-fold, 2.5-fold, twofold and twofold increased risk for mortality, respectively. Previous studies have identified that underlying diseases are one of the risk factors for mortality [27,28]. In the present study, although underlying diseases were associated with in-hospital death, they were not detected as independent predictors in multivariate analysis.  There is an increased number of studies investigating clinical deterioration and mortality predictors of COVID-19 [27][28][29][30][31]. Acar et al. reported that 11% of COVID-19 patients (n = 75/709) died; in their study, the independent predictors of mortality were specific comorbidities, dyspnea, SpO2, hematocrit, CRP, aspartate aminotransferase and ferritin. They developed a novel score with the combination of these seven predictors in addition to age. In the study of Guner et al., 15.2% of COVID-19 patients (n = 104/686) transferred to the ICU [29]. In their final model, the independent predictors of the need for ICU transfer were SpO2, CRP, procalcitonin, lactate dehidyrogenase and troponin. Guner et al. reported a good predictive value in the ROC analysis (AUC = 0.93; CI = 0.90-0.95) [29].  Bayram et al. [30] developed a novel score named CAPA, which allows for the prediction of mortality and ICU admission in patients with COVID-19. They reported that the AUC values of the CAPA score in predicting mortality and ICU admission were 0.67 and 0.66, respectively. In our study, the AUC values of the SAD-60 score in predicting mortality and ICU admission were 0.776 and 0.763, respectively. However, these studies were conducted in single tertiary care centers. Liang et al. [31] established the COVID-GRAM score with a cohort of 1590 COVID-19 patients from 575 hospitals in China and demonstrated that the mean AUC was 0.88 (CI = 0.85-0.91) in the development cohort. Although most patients have mild or moderate disease, COVID-19 can progress to severe disease and result in acute respiratory distress syndrome, multiorgan failure, septic shock and death [2]. Therefore, early stratifying of COVID-19 patients based on disease severity is vital. CURB-65 has been the widely used scoring system for severity classification, outcome and mortality prediction of community-acquired pneumonia. NEWS2 has been recommended by the National Institute of Clinical Excellence (NICE) for the prediction of clinical deterioration in patients with COVID-19 [32]. However, although there are studies to identify risk factors for disease progression and to develop scoring models in patients with COVID-19, no concensus has been reached [18,[33][34][35]. In addition, previous reports do not identify cut-off values of continues variables [36] or have not used combined parameters similar to our previous report (blinded). Even if studies categorize continuous variables, they do not stratify patients according to mortality risk by scoring [37,38]. These issues cause difficulties in calculation of the risk by physicians. In the present study, a simplified nomogram was used to assess the risk of mortality in patients with COVID-19 pneumonia.  The SAD-60 score, which was derived from the model in the present study, could be helpful for detecting patients at high risk of clinical deterioration and mortality. This might improve patient outcomes by enhancing physicians clinical decision making. Indicators of inflammation could be useful for predicting prognosis in patients with COVID-19. Our biomarker-based model incorporated albumin and D-dimer. Recent studies have confirmed that these biomarkers provide substantive information about clinical deterioration and the risk of mortality [25,26,[38][39][40]. In addition, some studies revealed the role of albumin in COVID-19 prognostication reflecting both possible liver damage, inflammation and the nutritional status of patients [41,42].
This study has several strengths. First, this was a multicenter study conducted in six hospitals with 1013 patients with COVID-19. Second, different types of variables, such as multiple comorbidities, symptoms, vital signs and laboratory parameters, were included in the multivariate regression analysis. Moreover, as laboratory parameters were routinely tested in all six hospitals, we could collect biomarkers probably associated with disease severity. Third, we had a relatively a large sample size.
This study has several limitations. First, our study was retrospectively conducted. Second, external validation was not performed. The generalizability of the results might be limited even with this being a multicenter study. Therefore, we need new large-scale studies to further improve the robustness of this model. Last, we did not perform longitudinal evaluation of vital signs and laboratory parameters.
A part of this study was presented at IDWeek-2021. The abstract, Table 4 & Figure 3 were published in the journal Open Forum Infectious Diseases [43].

Conclusion
We created a simple prediction model based on two biomarkers, as well as the clinical features of age and SpO2, and demonstrated that the SAD-60 score has promising predictive capacity for mortality in hospitalized patients with COVID-19. Thus, patients with high risk scores at admission should be carefully monitored and preventive strategies should be implemented to reduce mortality.

Summary points
• The pandemic of COVID-19 continues to be a significant public health issue.
• In this retrospective multicenter study, the aim was to explore a novel risk score to predict mortality in hospitalized patients with COVID-19 pneumonia. In addition, the accuracy of the novel risk score with CURB-65, qSOFA and NEWS2 scores was compared. • A total of 1013 patients with COVID-19 were included. In-hospital death occurred in 124 (12.2%) patients.
• Multivariate analysis revealed that peripheral capillary oxygen saturation, albumin, D-dimer and age were independent predictors for mortality. • The mortality score model was given the acronym SAD-60, representing SpO2, Albumin, D-dimer, age ≥60 years.